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Sunday, May 10, 2026 2:00 - 5:00 pm

SC1: In silico and Machine Learning Tools for Antibody Design and Developability Predictions

Given the exciting pace in the evolution of machine learning tools towards antibody design and developability predictions, we plan to present an overview in this field specificity geared towards antibody design and developability predictions. There will be a live demo as well of few ML tools.

Topics to be covered include:

Overview of sequence, structure-guided, ML (machine learning) tools for developability and designs
Overview and demo of various ML tools from Oxford Protein Informatics Group (OPIG)
Antibody specific language models (Ablang - Olsen et al 2022, Ablang2 - Olsen et al 2024)
Antibody (and nanobody) structure prediction (ABodyBuilder2) Abanades et al 2023)
Therapeutic antibody profiling and developability evaluation (TAP - Raybould et al 2019, TAP2 - Raybould et al 2024)
Antibody sequence optimization with inverse folding (AntiFold - Hummer et al 2023)
In silico developability assessment: case studies

INSTRUCTOR BIOGRAPHIES:

Vinodh B. Kurella, PhD, Research Scientific Associate Director, Global Biologics, Takeda Pharmaceuticals, Inc.

Vinodh Kurella is a Research Scientific Associate Director in Biological Engineering and Antibody Discovery within Global Biologics at Takeda (Cambridge, USA). He utilizes structure guided and ML driven approaches for discovery, design (lead optimization) and developability for biologics. Previously he has worked at various biotech/pharma companies in different modalities such as Gene-therapy (Voyager Trx), Biologics (Merrimack Pharma) and CAR-T engineering (Intrexon/Precigen). His post-doctoral training was at Harvard Medical School/Dana Farber Cancer Institute (DFCI) in antibody engineering and his graduate training was from Louisiana State University (LSU-HSC) in the field of protein X-ray crystallography.

Tanmoy Sanyal, PhD, Principal Data Scientist, Large Molecule Discovery Group, Amgen

Tanmoy Sanyal, PhD is a Principal Data Scientist in Amgen's Large Molecule Discovery group, where he develops data-efficient machine learning models to re-engineer biologics for affinity and developability. Prior to joining Amgen, Tanmoy worked in computational design of half-life extenders for peptide-based formats at Novo Nordisk. He obtained his PhD in Chemical Engineering at University of Santa Barbara, California, and later worked as a postdoctoral scholar at University of California, San Francisco, developing Bayesian inference methods to determine macromolecular structure from chemical crosslink data.

Valentin Stanev, PhD, Associate Principal Data Scientist, AstraZeneca

Valentin Stanev received an M.S. in physics from Sofia University, Bulgaria in 2000, and a Ph.D. in physics from Johns Hopkins University in 2010. After a postdoctoral position at Argonne National Laboratory, he moved to the University of Maryland at College Park, where he eventually became an Associate Research Professor at the Department of Material Science and Engineering. In 2021 Dr. Stanev joined the Biopharmaceutical Development Department at AstraZeneca, where he is currently an Associate Principal AI Scientist. His research interests include applications of machine learning methods to predict the developability of biologics.

Ben Williams, PhD, Research Software Engineer, Department of Statistics, University of Oxford

I joined the Oxford Protein Informatics Group (https://opig.stats.ox.ac.uk/) in January 2025 as a research software engineer, supporting the development and deployment of the group's tools, including SAbDab, the Structural Antibodies Database. You can use and learn about many of OPIG's freely available tools and resources here: https://opig.stats.ox.ac.uk/webapps I have a doctorate in condensed matter physics from the University of Oxford and spent several years developing software and methods for data analysis at Diamond Light Source, the UK's national synchrotron X-ray source and electron microscopy facility.

SC2: AI-Driven Predictive Preclinical Models: Rethinking the Role of Animal Testing

AI-driven predictive models are emerging as powerful tools to support preclinical IND activities by simulating human biology and forecasting pharmacology, toxicity, and immunogenicity outcomes. These approaches, consistent with NAM guidance, reduce reliance on animal testing by providing earlier, more human-relevant insights into safety and efficacy. As a result, animal studies can be repositioned as confirmatory rather than exploratory, improving translational relevance and regulatory alignment.

Topics to be covered include:

Regulatory Context & NAM Alignment

- Overview of FDA/EMA adoption of New Approach Methodologies (NAMs) in IND-enabling studies

AI-Integrated Toxicology Platforms

- Machine learning models predicting organ toxicity, off-target effects, and dose thresholds

in silico Immunogenicity & Safety Modeling

- Tools for predicting ADA risk, cytokine release, and innate immune activation

Digital Twin & Virtual Human Systems

- Computational models simulating PK/PD, metabolism, and disease progression

Reduction of Animal Testing

- Case studies where AI-driven data supported, reduced animal use in IND submissions

Multi-Omics & Systems Biology Integration

- Using genomics, transcriptomics, proteomics, and metabolomics to train predictive AI models

Future Landscape

- Roadmap for embedding AI models as a standard preclinical component to accelerate IND readiness

Agenda:

2:00 pm Introduction to NAM Guidance

Pooja Khanna, PhD, Senior Scientist, Merck

2:15 pm AI/ML Based Prediction Models for Predicting Clinical Immunogenicity During Preclinical Development

Guilhem Richard, PhD, CTO, EpiVax

2:40 pm Computational/QSP Based Models to Preclinical IND Enabling Activities

Panagiota (Pegy) Foteinou, PhD, Senior Director, Preclinical and Early Development, Bristol Myers Squibb

3:05 pm Refreshment Break

3:20 pm Use of in silico and in vitro Human Relevant Assays and Related AI/ML Based Models to Support Preclinical IND Enabling Activities

Jochem Gokemeijer, PhD, Distinguished Scientist, Biologics, Johnson & Johnson

3:45 pm Computational/QSP Based Models

Timothy Hickling, PhD, Consultant, Quasor Ltd.

4:10 pm 2D and 3D Skin and Specialized Models to Develop ML Algorithms for Understanding Drug Disposition and Safety Risks in Preclinical Stage of Development

Sathy Balu-Iyer, PhD, Professor, Pharmaceutical Sciences, SUNY Buffalo

4:35-5:00 pm Panel Discussion and Key Takeaways

Vibha Jawa, PhD, Chief Scientific Officer, Epivax Inc.

INSTRUCTOR BIOGRAPHIES:

Sathy Balu-Iyer, PhD, Professor, Pharmaceutical Sciences, SUNY Buffalo

Dr. Sathy Balu-iyer is a Professor in the Department of Pharmaceutical Sciences at SUNY - University at Buffalo and is an Associate Dean for Research, School of Pharmacy and Pharmaceutical Sciences. He is an elected fellow of American Association of Pharmaceutical Scientists (FAAPS). His interdisciplinary research involves biophysical, immunological and Pharmacokinetic/dynamic approaches to rationally develop immunotherapy modalities. He is recipient of NIH sponsored projects as principal investigator. He has authored about 100 peer-reviewed publications, over 200 meeting abstracts/presentations and is an inventor over 50 patents/patent applications. The Awards he received include Biotechnology Innovation Award from American Association of Pharmaceutical Scientists (AAPS) and Inventor of the year Award from Niagara Frontier Intellectual Property Law Association. His University awards include University at Buffalo Sustained Achievement Award and Teaching innovation Award. He is one of the Editors of Journal of Pharmaceutical Sciences and serves on editorial boards of several international journals including Biodrugs. He is a member of American Association of Pharmaceutical Scientists AAPS and American Association for the Advancement of Science AAAS.

Panagiota (Pegy) Foteinou, PhD, Senior Director, Preclinical and Early Development, Bristol Myers Squibb

Jochem Gokemeijer, PhD, Distinguished Scientist Biologics, Biologics Discovery, Johnson & Johnson

Jochem is currently at Johnson and Johnson focused on non-clinical immunogenicity of biologics Before that he was at Bristol-Myers Squibb for 14 years in different roles of responsibility focused on biologics drug development. For the last 8 years he has been focused on building a group for pre-clinical immunogenicity risk assessment and mitigation. He received his training at the University of Groningen and the Dana Farber Cancer Institute.

Timothy Hickling, PhD, Consultant, Quasor Ltd.

Tim has 15 years’ experience contributing to immunogenicity risk and mitigation strategies for large molecules and advanced therapies at Roche and Pfizer, from early discovery projects to those in clinical development and post-marketing. During the last ten years he has contributed immunology expertise to the development of an in silico immunogenicity model, with the purpose of improving predictions of clinical immunogenicity for drug candidates. Tim previously worked on vaccine development and holds a PhD in Immunology from the University of Oxford.

Vibha Jawa, PhD, Chief Scientific Officer, Epivax Inc.

Vibha brings more than 20+ years of experience in supporting biologics, vaccine development, and gene therapy with contributions to multiple IND, BLA, and MAA filings. She is a recognized leader in the area of Bioanalysis and Immunogenicity with more than 50 peer-reviewed publications. In her current role as an Executive Director for Biotherapeutics Bioanalysis at Bristol Myers Squibb, Vibha is responsible for leading biotherapeutic and cell therapy bioanalytical (BA) functions.

Pooja Khanna, PhD, Senior Scientist, Merck

Guilhem Richard, PhD, CTO, EpiVax Inc.

Guilhem Richard, Ph.D., is the Chief Technology Officer of EpiVax, Inc. and has over 10 years of experience in computational immunology and vaccinology. Dr. Richard joined the EpiVax immunoinformatics team in 2014, developing new models for understanding the interaction between the immune system and protein sequences, while supporting EpiVax’s commercial and research programs. He spearheaded the development of a new computational platform for the development of personalized, neoantigen-based cancer vaccines (Ancer), and conducted subsequent translational work at EpiVax’s subsidiary company, EpiVax Therapeutics, Inc., from 2019 to 2024 where he served as Chief Scientific Officer/Chief Technology Officer. Dr. Richard has been leading innovation efforts at EpiVax since 2024 and is overseeing the development of its next generation of immunoinformatics tools. Dr. Richard holds a Ph.D. in Bioinformatics from Boston University and a M.Eng. in Bioinformatics and Modeling from the National Institute of Applied Sciences (INSA) of Lyon, France.

SC3: Challenges and Opportunities in Solid Tumor and Autoimmune Disease Therapeutics

This course offers advanced insights into developing next-generation immunotherapies for solid tumors and autoimmune diseases, focusing on identifying new targets, therapeutic methods, and emerging biology. It includes detailed analyses of the solid tumor microenvironment and the autoimmune diseases space, addressing challenges and showcasing successful therapeutic strategies across T cell engagers, blocking bispecific antibodies, ADCs, CAR-Ts, radioligand therapy and targeted protein degraders.

Identify and develop next-generation immunotherapies for solid tumors and autoimmune diseases
Analyze the solid tumor microenvironment, discussing successful therapies such as T cell engagers, blocking bispecific antibodies, ADCs, CAR-Ts, Radioligand therapy, and Targeted Protein degraders
Examines autoimmune disease biology and therapeutic development, integrating approaches like immune target blockade and autoantigen tolerizing.
Highlights the application of machine learning and generative AI in discovering novel therapeutic targets and expediting therapeutic development.
Addresses the challenges and provides case examples of cutting-edge therapeutic approaches in both cancer and autoimmune diseases

INSTRUCTOR BIOGRAPHIES:

Tony R. Arulanandam, DVM, PhD, CEO and Founder, Synaptimmune Therapeutics

Tony Arulanandam, DVM, PhD, is CEO /Founder Synaptimmune Therapeutics, Developing the next generation "Conditionally active and Costimulatory T cell engagers (TCE)" for Autoimmune and Solid tumor indications. Senior Vice President and Head of Preclinical Research and Development at Cytovia Therapeutics focused in developing NK Cell engager bispecific antibodies and iPSC derived CAR-NK therapies for cancer. He is also the Co-Founder of NextPoint therapeutics, an MPM capital-funded IO checkpoint immunotherapy company. He is an immunologist with 20+ years of research and development experience developing multiple immunotherapies for autoimmune/inflammatory diseases and cancer (5 BLAs and multiple INDs). He is also currently a mentor for postdocs at the Dana-Farber Cancer Institute through the Post-Graduate Association.

SC4: Unlocking Immunity: Mastering Epitope Analysis and Prediction with IEDB and CEDAR Tools & Insights

This short course offers an in-depth introduction to the Immune Epitope Database and Analysis Resource (IEDB) and Cancer Epitope Database and Analysis Resource (CEDAR), designed to help scientists harness their full potential for immunological research. Participants will receive two focused presentations-one on navigating the IEDB (https://iedb.org/) and CEDAR (cedar.iedb.org) databases and another on using powerful prediction and analysis tools, including both the classic Analysis Resource (http://tools.iedb.org/main/) and the cutting-edge Next-Generation Tools (https://nextgen-tools.iedb.org/). The course will feature live demonstrations to guide attendees through real-world applications of these resources, empowering them to integrate epitope data and predictive modeling into their own research workflows.

Topics to be covered:

Overview of the IEDB and CEDAR database structure, content, and how to search for epitope-related data
Introduction to the classic Analysis Resource: tools for epitope analysis and prediction
Walkthrough of the Next-Generation Tools to create prediction pipelines for advanced scientific research
Live demonstrations showing how to apply all IEDB resources to real-life scientific problems, including predicting cancer epitopes and de-immunizing protein antigens
Practical guidance on integrating IEDB resources into your own research projects and experimental design

Benefits of attending:

Gain a comprehensive understanding of how to navigate and extract data from the IEDB and CEDAR database
Learn to use both classic and next-generation epitope prediction tools to enhance your research capabilities, including predicting cancer epitopes and de-immunizing protein antigens
See real-world examples of how IEDB tools can be applied to address complex immunological research questions
Develop the skills to build and customize epitope prediction pipelines for your specific research needs
Leave with practical knowledge and confidence to incorporate IEDB resources into experimental planning and data analysis

INSTRUCTOR BIOGRAPHIES:

Nina Blazeska, Senior Project Manager, IEDB and CEDAR Resources, La Jolla Institute for Immunology

Nina Blazeska is a Senior Project Manager with over eight years of experience leading cross-functional teams in science research, technology, and financial sectors. At present, Nina leads a portfolio of immunology-based projects at the La Jolla Institute for Immunology with Principal Investigators, Dr. Alessandro Sette and Dr. Bjoern Peters, including the Immune Epitope Database (IEDB - iedb.org) and the Cancer Epitope Database and Analysis Resource (CEDAR - cedar.iedb.org). These databases and bioinformatic tools are used to further our understanding of cancer, autoimmune conditions, infectious diseases, allergies, and transplants. With an MBA in Business Analytics and a strong commitment to continuous improvement, Nina aims to make science accessible to all people by bridging expert and non-expert audiences and fostering community collaborations.

Zeynep Kosaloglu-Yalcin, PhD, Instructor, La Jolla Institute for Immunology

Dr. Zeynep Kosaloglu-Yalçin is an Instructor and computational cancer immunologist at the La Jolla Institute for Immunology. She develops advanced machine learning methods and bioinformatics tools to predict T cell recognition of epitopes and support the development of personalized immunotherapies. As the tools lead for the Cancer Epitope Database and Analysis Resource (CEDAR), she designs user-friendly, accessible resources that empower researchers across disciplines to explore cancer immunity at scale. Her work bridges computational immunology and clinical oncology by integrating large-scale patient data with a focus on translational applications. Dr. Kosaloglu-Yalçin works closely with clinicians, immunologists, and data scientists to perform multidisciplinary, integrated analyses with the goal of advancing precision cancer immunology.

SC5: Safety & Efficacy of Bispecifics and ADCs

Bispecific immunotherapies and ADCs are the two most rapidly advancing therapeutics in the war against cancer. However, efficacy and safety challenges limit their therapeutic effectiveness in resistant and refractory cancers. The short course will discuss five rights of the targets, effector arms, and constructs for attaining the best therapeutic index for bispecifics and ADCs. Special focus will be on attaining the best efficacy with minimal toxicities.

Bispecific immunotherapies and ADCs are two of the most rapidly advancing therapeutics in the fight against cancer. However, efficacy and safety challenges limit their therapeutic effectiveness in resistant and refractory cancers. The short course will discuss the five rights of the targets, effector arms, and constructs for achieving the optimal therapeutic index for bispecifics and ADCs. Special focus will be on attaining the best efficacy with minimal toxicities.The short course will discuss:

Bispecific and ADC landscape assessment and unmet medical needs
Efficacy and safety challenges originating from poorly constructed ADCs
Five rights of the targets, effector arms, and constructs for attaining the best therapeutic index for bispecifics and ADCs
Minimizing toxicities of bispecifics and ADCs
Translational aspects of bispecific and ADC development

INSTRUCTOR BIOGRAPHIES:

Rakesh Dixit, PhD, DABT, CEO & President, Bionavigen Oncology, LLC; CSO, TMAB Therapeutics, Regio Biosciences

Rakesh Dixit is an accomplished executive, inventor, and scientist with over 35 years of success with top biotechnology and pharmaceutical companies, including Merck, Johnson & Johnson, and Medimmune - AstraZeneca. Currently, he is President and CSO of Regio Biosciences and Bionavigen, LLC. He is a Board Member of Regio Biosciences and a key member of multiple scientific advisory boards. Rakesh is also a chief adviser and consultant for more than 20 companies worldwide. His biopharmaceutical peers selected Rakesh as one of the 100 Most Inspiring People in the Pharmaceutical Industry by PharmaVOICE in 2015. Rakesh received the Most Prestigious Award of Long-Standing Contribution to ADCs by World ADC (Hanson-Wade), 2020. From 2006 to 2019, Rakesh was a Global Vice President of the Biologics R&D at Medimmune - AstraZeneca. Rakesh has unique expertise in developing biologics (e.g., monoclonal antibodies, bispecific biologics, antibody-drug conjugates, fusion proteins, peptides, gene and cell therapies, etc.) and small-molecule biopharmaceuticals. His areas of expertise include discovery, early and late preclinical development, safety assessment, DMPK, and translational sciences. Dr. Dixit conducted extensive graduate and post-graduate training in Pharmacology/Toxicology-Biochemistry with both Indian and USA institutions (e.g., Case Western Reserve University, Medical College of Ohio, University of Nebraska) and is a Diplomate and Board Certified in Toxicology from the American Board of Toxicology, Inc. since 1992.

Tuesday, May 12, 2026 6:30 - 9:00 pm

SC6: Developability of Bispecific Antibodies

Bispecific antibodies are a rapidly growing and clinically validated class of antibodies with marketed drugs and multiple candidates in clinical trials. Targeting multiple antigens in a synergistic manner can confer enhanced therapeutic benefit and potentially uncover novel biological mechanisms. However, multiple formats and a tedious candidate selection process to select functional and developable bispecific antibodies makes such programs cumbersome. This short course highlights the rapid growth in the field, therapeutic applications, and focuses on challenges with discovery and development of bispecific antibodies. We will use an approved bispecific antibody as a case study to understand the varied aspects of discovery and development of bispecific antibody programs.

Topics to be covered:

Introduction to bispecifics and bispecific formats
Therapeutic applications of bispecific antibodies
Developability of bispecifics
Case study: discovery and development of an FDA-approved bispecific antibody

INSTRUCTOR BIOGRAPHIES:

Nimish Gera, PhD, Independent Consultant

Nimish Gera is an independent consultant and biotech executive with broad experience across antibody-based modalities including mono- and bispecific antibodies, protein fusions, and antibody-drug conjugates (ADCs) across several therapeutic areas such as oncology, immunology, autoimmune, and rare diseases. He has held scientific and/or leadership roles at companies ranging from early-stage startups like Mythic Therapeutics and Oncobiologics to large organizations such as Alexion Pharmaceuticals and Genentech. With more than fifteen years in drug development, Nimish has successfully advanced complex bispecific and ADC programs from concept through preclinical and early clinical stages. He serves as Associate Editor of the journal mAbs, hosts the Chain Protein Engineering podcast, and teaches the Developability of Bispecific Antibodies short course at the PEGS Boston and Europe conferences. Nimish has a proven track record of bringing multiple drug candidates to clinical trials, publishing peer-reviewed articles, building IP portfolios, and chairing national and international meetings on antibody therapeutics. He holds a PhD in Chemical and Biomolecular Engineering from North Carolina State University and a B.Tech in Chemical Engineering from the Indian Institute of Technology, Guwahati.

SC7: Targeting the Target: Aligning Target and Biologic Format Biology to Achieve Desired Outcomes

Receptor-ligand interactions have co-evolved to maintain specificity of downstream signaling. However, biologics are not natural ligands and, therefore, different biologics to the same target (receptor or ligand) can have distinct outcomes. Recent advances in various high-throughput analytical technologies, biologic-based therapeutic formats, and our understanding of disease heterogeneity are & will challenge us to “re-evaluate” our discovery and development paradigm(s). In this course we will explore, with examples, potential avenues on how to apply these new technologies/understanding to select “better” lead candidates to achieve “better” desired outcomes.

Topics to be covered:

Introduction to the “components of success paradigm”
Underlying concepts and examples of one target and multiple functions/outcomes
How emerging technologies are and could impact:

- Understanding target biology, lead selection, and discovery/development paradigms

- Target space for bispecific, ADCs, and other therapeutic formats/concepts

Case studies: (i) evaluating functional impact of different mAbs to the same target (target/mAb biology): (ii) designing biologic molecules to develop functional assays to assess novel/emerging target biology and potentially develop novel therapeutics

INSTRUCTOR BIOGRAPHIES:

Tariq Ghayur, PhD, Tariq Ghayur Consulting, LLC; Entrepreneur in Residence, FairJourney Biologics

Dr. Ghayur retired from AbbVie (July 2021) and works as an independent consultant. He has 30+ years’ experience leading multi-disciplinary and cross-therapeutic area Biologics discovery programs and developing novel Biologics platforms. Several biologics programs resulted in clinical development candidates. Dr. Ghayur led the team that pioneered the discovery and development of the Dual - variable - Domain -Ig (DVD-Ig) and other multi-specific platforms. Dr. Ghayur also led the team that defined the uptake, intracellular trafficking, and lysosomal degradation of anti-TNF mAbs/DVD-Ig, resulting in the concept of anti-TNF-ADC (next-Gen anti-TNF). In addition, Dr. Ghayur proposed and helped implement several corporate-wide (Abbott & AbbVie) initiatives to foster cross-functional/cross-TA collaborations to bring forward innovative concepts/programs.

SC8: The Dark Proteome: Unlocking Novel Targets for Next-Generation Biologics

The dark proteome-comprising over 250,000 novel proteins from noncoding regions-represents an untapped frontier for therapeutic discovery. This course provides protein engineers and drug developers frameworks to identify and exploit dark antigens: cryptic, noncanonical, and post-translationally modified epitopes that enable novel-binding interfaces. Participants will learn AI-driven discovery methods, target validation strategies, and design principles for engineering biologics against hidden epitopes, with applications across oncology, infectious disease, and autoimmunity.

The next generation of biologics depends on our ability to access the vast, largely unexplored "dark proteome"-comprising over 250,000 potential novel proteins encoded by the 98% of the human genome once dismissed as "junk".

This short course provides protein engineers and therapeutic developers with a comprehensive framework for understanding, identifying, and exploiting these hidden targets through the integration of AI-driven discovery, advanced proteogenomics, and rational design strategies. With traditional protein-coding genes becoming increasingly crowded and drug discovery facing unprecedented challenges, the dark proteome represents an opportunity for first-in-class therapeutics. This course will equip participants with both the conceptual understanding and practical tools to navigate this emerging frontier, with special emphasis on "dark antigens"-cryptic, noncanonical, and post-translationally modified epitopes that enable novel binding interfaces and expanded therapeutic specificity.

INSTRUCTOR BIOGRAPHIES:

Sudhakaran Prabakaran, Co-Founder & CEO, NonExomics

Dr. Sudhakaran Prabakaran is a computational biologist and biotechnology entrepreneur pioneering the application of AI and multi-omics integration to unlock the "dark proteome" for therapeutic discovery. Currently, he is CEO and Co-Founder of NonExomics Inc. and Associate Teaching Professor at Northeastern University. He serves on scientific advisory boards and has mentored over 50 students, postdocs, and researchers across academia and industry. His landmark 2014 Nature Communications publication provided the first large-scale proteomic evidence of translation from "noncoding" RNAs, establishing the dark proteome as a therapeutic frontier. His 2022 Molecular Psychiatry work revealed novel proteins in human accelerated regions providing new leads for schizophrenia and bipolar disorder. His research has resulted in six patent applications across oncology, neuropsychiatry, and rare diseases, and has been featured in Science, Bloomberg, Inside Precision Medicine, and The Times. From 2016 to 2021, Dr. Prabakaran was Assistant Professor and Fellow at the University of Cambridge, where he led research on novel open reading frames and their disease relevance. He has authored a comprehensive book, Eclipsed Horizons: Unveiling the Dark Genome (World Scientific Publishing, 2025), and has received recognition including the Cambridge-Hamied Visiting Lectureship, Illumina Accelerator acceptance, and AWS Research Award. Dr. Prabakaran has expertise spanning proteogenomics, systems biology, machine learning, and translational therapeutics development. His areas of focus include dark proteome target discovery, AI-driven drug development, immunotherapy design, and precision medicine. Dr. Prabakaran received his Ph.D. in Systems Neuroscience from the University of Cambridge and completed postdoctoral training in Systems Biology at Harvard Medical School.

SC9: Automation in Action: Hands-on, Liquid Handling for Protein & Antibody Engineering

This short course introduces the principles, techniques, and key considerations of automated liquid handling. Participants will learn how to develop and optimize an automated assay through an interactive experience and live demonstration. The course is offered by experts from the Institute for Protein Innovation (IPI), a leader in applying cutting-edge automation to advance protein science. Participants are encouraged but not required to attend Friday off-site hands-on session. Please note: *A laptop is required to participate

Participants will:

Discover automated liquid handling tools, techniques, and best practices
Engage in an interactive demonstration of an automated liquid handler.

Who should attend:

Students and researchers who want to learn the basics of automation systems. Researchers who are interested in setting up their own laboratory automation systems and workflows. Computational scientists who are interested in exploring how large data sets are collected for in silico protein/antibody modeling.

Please note: *A laptop is required to participate

Optional Off-site Hands-on Practicum

Friday, May 15

1:30 - 4:30 pm

Registered participants of the short course may deepen their experience through further training at the nearby IPI (Harvard Medical School campus). This course involves working in teams with robots to implement the assay learned and optimize liquid handling parameters, a key skill for real world application. Particpants will then tour IPI, observing the operation of more sophisticated liquid-handling systems.

(Prerequisite: Automation in Action: Hands-on, Liquid Handling for Protein & Antibody Engineering Short Course Attendance)

Participants will:

Gain hands-on experience setting up a liquid handling robot.
Explore how to apply automation to their own research workflows.
Tour IPI’s automation facilities and observe live demonstrations of integrated robotic systems.

Registered short course participants are welcome to attend the Friday practicum at the Institute of Protein Innovation. However, space for the practicum is limited to 8 participants and will be offered on a first-come, first-served basis through a separate RSVP.

Registered practicum participants will be transported from the Omni Boston to IPI.
Engage in an interactive demonstration of an automated liquid handler.

INSTRUCTOR BIOGRAPHIES:

Curtis Walton, PhD, Director of Automation and Process Optimization, Institute for Protein Innovation

Curtis Walton, Ph.D. is the Director of Automation and Process Optimization at the Institute for Protein Innovation (IPI). He brings deep expertise in laboratory automation, bioinformatics, and protein engineering, with a strong track record of building scalable workflows that accelerate scientific discovery. Curtis holds a Ph.D. in Chemistry from the University of Ottawa, where he developed novel biocatalysts for pharmaceutical applications. At IPI and in previous roles, he has led multidisciplinary teams and spearheaded the integration of cutting-edge automation platforms, transforming research pipelines through innovative, data-driven approaches.

Eloy Salinas, Senior Lab Automation Engineer, Institute for Protein Innovation

As a Senior Lab Automation Engineer at the Institute for Protein Innovation, and with a Bachelor of Science in Robotics Engineering from UC Santa Cruz, I have a strong background in designing, onboarding, and maintaining integrated systems. My experience spans developing methods for various lab automation platforms and prototyping custom robotic solutions. I thrive on consulting the feasibility of automating assays and coding scripts to connect lab instruments to LIMS, enabling automatic data visualization. My previous roles involved designing real-time software and hardware control applications for field robots, integrating robots into customer applications, and significantly improving testing efficiency through automation. With a foundation in equipment engineering, including PLC programming and hardware design, and software engineering focusing on GUI development and legacy system upgrades, I bring a comprehensive skill set to tackle complex automation challenges.

SC10: Best Practices and Advanced Applications for Label-Free Interaction Analysis in Therapeutic Antibody Discovery

This short course will provide simple guidelines for best practices of interaction analysis using commonly-used commercial label-free biosensors in the characterisation of therapeutic antibodies. We will focus mainly on the use of surface plasmon resonance (SPR) and biolayer interferometry (BLI). First, we will address best practices for generating high-quality binding kinetic and affinity data. Then we will do a deep dive into epitope binning. A basic knowledge of interaction analysis is assumed, but "all-comers" should find this course helpful. We will review several case studies together to reinforce these concepts.

Topics covered will include:

BINDING KINETICS:

Optimizing experimental setup including the influence of reagent quality, assay orientation, immobilization method, and surface capacity
Corroborating surface-based measurements with solution ones

EPITOPE BINNING:

Assay formats
Bin definition
Throughput Nuanced binning (antigen heterogeneity, asymmetry, and displacement)

INSTRUCTOR BIOGRAPHIES:

Yasmina Abdiche, PhD, Senior Vice President, Exploratory Research, OmniAb Inc.

Yasmina is an internationally recognized and innovative scientific leader in the field of antibody discovery and biosensor technology with twenty years of experience in protein engineering and biopharma. She has authored over 50 peer-reviewed publications, had 25 patents granted in the therapeutic antibody space including a market-approved drug for migraine (Ajovy) and a Phase 3 investigational drug for bladder cancer (Sasanlimab), presented over 60 times as an invited speaker globally, and has been involved in numerous industry-wide collaborations and scientific advisory groups. After a twelve-year career at Pfizer where she held positions of increasing responsibility from Principal Scientist to Research Fellow, more recently, Yasmina has held senior management roles at biotechnology companies and contract research organizations including Carterra (CSO), ImmunoPrecise Antibodies (CSO), ALX Oncology (VP Protein Science), Revelar (CSO and Co-Founder), and FairJourney Biologics (CTO). During her time as CSO at Carterra, she co-founded its antibody screening biosensor platform (the LSA) which has helped transform label-free interaction analysis in early-stage drug discovery. Yasmina has a master's degree in chemistry and a PhD in biological chemistry from Oxford University and did post-doctoral studies in biophysical interaction analysis at the University of Utah.

* 不測の事態により、事前の予告なしにプログラムが変更される場合があります。

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